Bart Vandekerckhove, co-founder at Raito, discusses the importance of data access management and data security. Topics covered include granular access management in cloud databases, maintaining a Chinese wall, the impact of AI on data security, anomaly detection, the role of AI in security culture, common mistakes in data security, and improving data security and culture.
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Quick takeaways
Striking a balance between data access and data security is crucial for organizations to drive growth while protecting customer trust and complying with regulations.
Data access management now requires managing access at the dataset level, implementing controls based on table, row, or file levels in order to maintain security and privacy in a centralized data environment.
Deep dives
Data Access and Security Balance
In today's competitive landscape, companies rely on data as a strategic asset to drive innovation, better products, and improved services. However, striking a balance between data access and data security is crucial. Too much restriction can hamper innovation, while being too permissive poses security risks. Organizations need to find this equilibrium to drive growth while protecting customer trust and complying with regulations.
Understanding Data Access Management
Data access management is a critical area of data security. Traditionally, access management was focused on perimeter-based controls, granting access to everything within a database or application. However, with the migration to the cloud and the increase in data sets, a more granular approach is needed. Data access management now requires managing access at the dataset level, implementing controls based on table, row, or file levels. This shift is necessary to maintain security and privacy in a centralized data environment.
Benefits of Effective Data Access Management
Effective data access management not only safeguards privacy and security but also offers productivity benefits. By granting precise access permissions, organizations can ensure data quality, prevent accidental mistakes, and provide guardrails for data engineers and analysts. Additionally, limiting access to relevant data reduces information overload, enabling data workers to focus on the data they actually need for their tasks. These measures enhance productivity while maintaining security.
Roles and Processes in Data Access Management
Implementing successful data access management involves different teams and roles. The data architect determines the tools and frameworks, while data engineers integrate access management into data products. Data owners play a crucial role in approving access requests, ensuring compliance with policies. In mature organizations, data governance, information security, and data privacy teams collaborate to define policies, monitor compliance, and manage access at a granular level. The involvement of these roles is essential to establish effective data access management.
Data used to be the exhaust of our work activities, until we started seeing the value it can provide. Today, data is a strategic asset, used to gain a competitive advantage and well guarded from those that might use it to harm others. With this change in attitude, how we access and safeguard our data has improved massively. However, data breaches are not a thing of the past, and with the advent of AI, many new techniques for maliciously accessing data are being created. With the extra importance of data security, it is always pertinent to iterate on how we keep our data safe, and how we manage who has access to it.
Bart Vandekerckhove is the co-founder and CEO at Raito. Raito is on a mission to bring back balance in data democratization and data security. Bart helps data teams save time on data access management, so they can focus on innovation. As the former PM Privacy at Collibra, Bart has seen first hand how slow data access management processes can harm progress.
In the full episode, Richie and Bart explore the importance of data access management, the roles involved in data access including senior management’s role in data access, data security and privacy tools, the impact of AI on data security, how culture feeds into data security, the challenges of a creating a good data access management culture, common mistakes organizations make, advice for improving data security and much more.